Optimal chiller loading for energy conservation using a new differential cuckoo search approach

The electrical energy consumption in a multi-chiller system increases if the chillers are managed improperly, therefore significant energy savings can be achieved by optimizing the chiller operations of heating, ventilation and cooling systems. Recently, optimization methods for optimal chiller loading have been proposed. In general, the aim of the optimization problem is to minimize chillers energy consumption keeping the cooling demand satisfied. As an efficient optimization method, the CSA (cuckoo search algorithm) has been proposed for solving continuous parameters optimization problems. CSA is based on the obligate brood-parasitic behavior of some cuckoo species in combination with the Lévy flight behavior of some birds and fruit flies. Preliminary studies show that it is promising and could outperform existing algorithms. This paper proposes a new CSA approach using differential operator (DCSA) to solve the optimal chiller loading design problem. The results of optimal chiller loading are analyzed on three case studies taken from literature to confirm the validity of the proposed algorithm. Simulations using case studies are presented and compared with the best known solutions. The comparison results with the classical CSA and other optimization methods demonstrate that the proposed DCSA (differential CSA) proves to be an effective and efficient at locating promising solutions in terms of minimum energy consumption.